An embodiment relates generally to autonomously developing ontologies of product function and failure documentation.
In system development process, design requirements such as design failure mode effects analysis (DFMEA) and elemental function-failure design method (EFDM) utilize functional similarity to design products and with a knowledge base of the failures that can occur with design characteristics. However, automation of integrating field data and identification of new failure modes rely on pre-existing data structures and “humans” in the loop during execution of the documents. Typically, a pre-defined ontology and/or legacy documents are required to provide classification structures. In addition, user intervention is required to process newly identified failure modes. As a result, synthesis of heterogeneous data in documents such as DFMEA research is a challenging and time-intensive task since iterative human work is required to process data beyond a scope of the prior work products. As a result, no techniques are currently available to compare document semantic similarity between heterogeneous data. Under current techniques, without failure data and prior knowledge, most estimations for completing rankings in the documents would require subject guessing on the part of the human.